Note : Les descriptions sont présentées dans la langue officielle dans laquelle elles ont été soumises.
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SPEECH RECOGNIZER
BACKGROUND OF THE INVENTION
The present invention relates to improvements
in speech recognizes reference patterns.
As a method of realizing speech recognizes
which are capable of ready alteration of
vocabularies presented for recognition, a method
which uses context-dependent phone reference
patterns has been extensively utilized. In this
method, a reference pattern of a given word
presented for recognition can be produced by
connecting context-dependent phone reference
patterns of corresponding phone expressions. A
context-dependent phone reference pattern of each
phone (which is designated as a set of three
elements, i.e., a preceding phone, the subject phone
and a succeeding phone), is produced by making
segmentation of a number of pieces of speech data
collected for training in phone units, and averaging
selectedly collected phones that are in accord
inclusive of the preceding and succeeding phones.
Such method is described in, for instance, Kai-Fu
Lee, IEEE Transactions on Acoustics, Speech, and
Signal Processing, 1990, Vol. 38, No. 4, pp.
599-609. In this method, a speech data base that is
used for producing a context-dependent phone
reference pattern, is provided separately from the
speech recognizes, and it is used only when
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producing the reference pattern.
Fig. 5 shows a case when producing a
context-dependent phone reference pattern from
speech data corresponding to a phone train "WXYZ" in
the speech data base. Referring to Fig. 5, "X (W,
Y)" represents a context-dependent phone reference
pattern of the phone X with the preceding phone W
and the succeeding phone Y. When identical
context-dependent phones appear in different parts
of speech data, their average is used as the
reference pattern.
In the case where a phone reference pattern is
produced by taking the contexts of the preceding and
succeeding one phone into considerations by the
1~ prior art method, including the case shown in Fig.
5, even if there exist speech data in the speech
data base that contain the same context as the phone
in a word presented for recognition inclusive of the
preceding and succeeding two phones, are not
utilized at all for recognition. In other words, in
the prior art method a reference pattern is produced
on the basis of phone contexts which are fixed when
the training is made. In addition, the phone
contexts to be considered are often of one preceding
phone and one succeeding phone in order to avoid
explosive increase of the number of combinations of
phones. For this reason, the collected speech data
bases are not effectively utilized, and it has been
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impossible to improve the accuracy of recognition.
SUMMARY OF THE INVENTION
An object of the present invention is therefore to
provide a speech recognizer capable of improving speech
recognition performance through improvement in the speech
reference pattern accuracy.
According to the present invention, there is
provided a speech recognizer comprising: a speech data
memory in which speech data and symbol trains thereof are
stored; a reference pattern memory in which are stored sets
each of a given partial symbol train of a word presented for
recognition and an index of speech data with the expression
thereof containing the partial symbol train in the speech
data memory; a distance calculating unit for calculating a
distance between the partial symbol train stored in the
reference pattern memory and a given input speech section;
and a pattern matching unit for selecting, among possible
partial symbol trains as divisions of the symbol train of a
word presented for recognition, a partial symbol train which
minimizes the sum of distances of input speech sections over
the entire input speech interval, and outputting the
distance sum data at this time as data representing the
distance between the input speech and t:he word presented for
recognition.
In a specific embodiment, the distance to be
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calculated in the distance calculating unit is the
distance between a given section corresponding to
the partial train of symbol train expression of
speech data stored in the speech data memory and the
given input speech section.
According to a concrete aspect of the present
invention, there is provided a speech recognizer
comprising: a feature extracting unit for analyzing
an input speech to extract a feature vector of the
input speech; a speech data memory in which speech
data and symbol trains thereof are stored; a
reference pattern memory in which are stored sets
each of a given partial symbol train of a word
presented for recognition and an index of speech
data with the expression thereof containing the
partial symbol train in the speech data memory; a
distance calculating unit for reading out speech
data corresponding to a partial train stored in the
reference pattern memory from the speech data memory
and calculating a distance between the corresponding
section and a given section of the input speech; a
pattern matching unit for deriving, with resect to
each word presented for recognition, a division of
the subject word interval which minimizes the sum
of distances of the input speech sections over the
entire word interval; and a recognition result
calculating unit for outputting as a recognition
result a word presented for recognition, which gives
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the minimum one of the distances between the input
speech data output of the pattern matching unit and
all the words presented for recognition.
Other objects and features will clarified from
the following description with reference to attached
drawings.
BRIEF DESCRIPTION OF THE DRAWINGS
Fig. 1 is a block diagram showing the basic
construction of this embodiment of the speech
recognizer;
Figs. 2 to 4 are drawings for explaining
operation of the embodiment of the speech recognizer
of Fig. 1; and
Fig. 5 is a drawing for explaining a prior art
speech recognizer in a case when producing a
context-dependent phone reference pattern from
speech data corresponding to a phone train "WXYZ" in
the speech data base.
DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENT
Now, an embodiment of the speech recognizer
according to the present invention will be described
with reference to the drawings: Fig. 1 is a block
diagram showing the basic construction of this
embodiment of the speech recognizer. Referring to
Fig. 1, a feature extracting unit 20 analyzes an
input speech inputted from a microphone 10, extracts
a feature vector and supplies the extracted feature
vector train to a distance calculating unit 30. The
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distance calculating unit 30 reads out speech data
corresponding to a partial train stored in a
reference pattern memory 50 from a speech data
memory 60 and calculates the distance between the
corresponding section and a given section of the
input speech. A pattern matching unit 40 derives,
with respect to each word presented for recognition,
a division of the subject word interval which
minimizes the sum of distances of the input speech
sections over the entire word interval. A
recognition result calculating unit 70 outputs as
the recognition result a word presented for
recognition, which gives the minimum one of the
distances between the input speech data output of
the pattern matching unit 40 and all the words
presented for recognition.
The operation of the embodiment of the speech
recognizer will now be described in detail with
reference to Figs. 2 to 4 in addition to Fig. 1.
According to the present invention, a number of
pieces of speech data and speech context phone
expressions thereof are prepared and stored in the
speech data memory 60. A reference pattern of a
word to be recognized is produced as follows:
(1) Partial trains of phone symbols of a word
presented for recognition, are prepared such that
they have given lengths (without overlap or
missing), as shown in Fig. 2.
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(2) Then, as shown in Fig. 3, all speech data
portions with phones containing a partial symbol
train among the speech data in a speech data base
are all picked up.
A combination of possible partial symbol trains
as divisions of a word presented for recognition and
corresponding speech data portions, is stored as a
reference pattern of the word presented for
recognition in the reference pattern memory 50. The
distance between the input speech data in the
pattern matching unit 40 and each word presented for
recognition, is defined as follows.
(a) A specific division of the word presented
for recognition is selected from the reference
pattern memory 50. The phone symbol train of the
word presented for recognition is denoted by W, and
the division of the symbol train into N partial
symbol trains is denoted by ~(1),~(2)...,
~a(N).
(b) From the speech data stored in the speech
data memory 6, with the symbol train containing
partial symbol trains each defined by a selected
division, a given segment of the speech is derived
as an acoustical segment of that partial symbol
train (Fig. 3).
Among the speech data with the symbol train
thereof containing partial symbol trains w(n), a
k-th speech data portion is denoted by A[~(n),k],
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(k = 1 to K(n)). The acoustical segment in a
section of the speech data from time instant a till
time instant z, is denoted by A[~(n),k,a,z].
(c) As shown in Fig. 4, distance between that
obtained by connecting acoustical segments and the
input speech, is calculated in accordance with the
sequence of partial symbol trains in the pattern
matching unit 40 by DP matching or the like.
Denoting the acoustical segment in a section of
the input speech from the time instant s till the
time instant t by X[s,t], the distance D is given by
the following formula (1).
D = ~Nn=ld(x[s(n),t(n)],A[w(n),k,~(n),in)]
... (1)
where d is the acoustic distance which is calculated
in the distance calculating unit 30.
For continuity, it is necessary to meet a
condition given as:
s(1) - 1
s(2) - t(1)+1
s(3) - t(2)+1
s(N) - t(n)+1
t(N) - T ... (2)
where T is the time interval of the input speech.
(d) By making the division of the symbol train
into all possible partial symbol trains in step (c)
and obtaining all possible sections (s,t,a,z) in the
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step (b), a partial symbol train which gives a
minimum distance is selected in a step (c), and this
distance is made as the distance between the input
speech and the word presented for recognition.
The recognition result calculating unit 70
provides as the speech recognition result a word
presented for recognition giving the minimum
distance from the input speech in the step (d) among
a plurality of words presented for recognition. In
the above way, the speech recognizer is operated.
It is possible of course to use the recognition
results obtainable with the speech recognizer
according to the present invention as the input
signal to a unit (not shown) connected to the output
side such as a data processing unit, a communication
unit, a control unit, etc.
According to the present invention, a set of
three phones, i.e., one preceding phone, the subject
phone and one succeeding element, is by no means
limitative, but it is possible to utilize all speech
data portions of words presented for recognition
with identical phone symbol train and context
(unlike the fixed preceding and succeeding phones in
the prior art method) that are obtained through
retrieval of the speech data in the speech data base
when speech recognition is made. As for the
production of acoustical segments, what is most
identical with the input speech is automatically
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determined at the time of the recognition. It is
thus possible to improve the accuracy of reference
patterns, thus providing improved recognition
performance.
Changes in construction will occur to those
skilled in the art and various apparently different
modifications and embodiments may be made without
departing from the scope of the invention. The
matter set forth in the foregoing description and
accompanying drawings is offered by way of
illustration only. It is therefore intended that
the foregoing description be regarded as
illustrative rather than limiting.
